A Study of an Adaptive Two-Phrase Signal Control Strategy for Resolving Conflicting Transit Signal Priority Calls

2014 ◽  
Vol 505-506 ◽  
pp. 1028-1036
Author(s):  
Liu Yi Gao ◽  
Xiao Jian Hu ◽  
Wei Wang ◽  
Xue Dong Hua

This paper presents the development and evaluation of an adaptive two-phrase signal control strategy to resolve conflicting Transit Signal Priority (TSP) requests. The strategy was designed to provide adaptive transit signal priority control, using vehicle systems and existing traffic control devices. In this paper, the strategys efficiency was tested using a micro-simulation software VISSIM and build one arterial road contains five intersections and serves more than twenty conflicting bus lines. The VAP module was used to control TSP of conflicting requests. In the simulation, actual data was used. Finally, control efficiency about adaptive signal control strategy is discussed. The results show that the presented strategy can improve the operation efficiency of bus corporations. This signal control strategy reduced the travel delay time by 33 % to 55% of transit, while has little impact on private traffic. The strategy shows promising results. In addition, with minor upgrades, it can be applied to any type of intersection.

Author(s):  
Yiheng Feng ◽  
Jianfeng Zheng ◽  
Henry X. Liu

Most of the existing connected vehicle (CV)-based traffic control models require a critical penetration rate. If the critical penetration rate cannot be reached, then data from traditional sources (e.g., loop detectors) need to be added to improve the performance. However, it can be expected that over the next 10 years or longer, the CV penetration will remain at a low level. This paper presents a real-time detector-free adaptive signal control with low penetration of CVs ([Formula: see text]10%). A probabilistic delay estimation model is proposed, which only requires a few critical CV trajectories. An adaptive signal control algorithm based on dynamic programming is implemented utilizing estimated delay to calculate the performance function. If no CV is observed during one signal cycle, historical traffic volume is used to generate signal timing plans. The proposed model is evaluated at a real-world intersection in VISSIM with different demand levels and CV penetration rates. Results show that the new model outperforms well-tuned actuated control regarding delay reduction, in all scenarios under only 10% penetrate rate. The results also suggest that the accuracy of historical traffic volume plays an important role in the performance of the algorithm.


2014 ◽  
Vol 505-506 ◽  
pp. 1046-1054 ◽  
Author(s):  
Liu Yi Gao ◽  
Xiao Jian Hu ◽  
Wei Wang ◽  
Shan Shan Yu

A good traffic signal design is one of the key solutions to many transportation problems. A two-way green wave control strategy for transit signal priority is reviewed and evaluated in this paper. Considering the traffic tidal phenomenon along the arterial roads during rush hours, a directional transit signal priority algorithm depend on the passenger flow has been developed for the coordination in signalized intersections. The algorithm provides signal timing plans for each intersection and the optimal bus speed along each section based on two-way bandwidth maximization. The strategy was designed to provide sectional control on transits, using electric signs and existing traffic control devices. In this paper, the strategys efficiency was evaluated using VISSIM micro-simulation along an arterial road which contains five intersections and serves more than ten bus lines. Actual data was used in the simulation. The simulation results show that the presented algorithm can effectively improve the operation efficiency of the transit system. This green wave control strategy reduced the number of stops by 34 % to 47 % and travel delay time by 27 % to 30% of the transit, while restricting the impact on vehicular traffic to the minimum. Moreover, the number of stops and travel delay time of vehicular traffic actually got a slight decrease. The algorithm shows promising results, and with minor upgrades, it can be applied to any type of intersection.


Author(s):  
S M A Bin Al Islam ◽  
Mehrdad Tajalli ◽  
Rasool Mohebifard ◽  
Ali Hajbabaie

The effectiveness of adaptive signal control strategies depends on the level of traffic observability, which is defined as the ability of a signal controller to estimate traffic state from connected vehicle (CV), loop detector data, or both. This paper aims to quantify the effects of traffic observability on network-level performance, traffic progression, and travel time reliability, and to quantify those effects for vehicle classes and major and minor directions in an arterial corridor. Specifically, we incorporated loop detector and CV data into an adaptive signal controller and measured several mobility- and event-based performance metrics under different degrees of traffic observability (i.e., detector-only, CV-only, and CV and loop detector data) with various CV market penetration rates. A real-world arterial street of 10 intersections in Seattle, Washington was simulated in Vissim under peak hour traffic demand level with transit vehicles. The results showed that a 40% CV market share was required for the adaptive signal controller using only CV data to outperform signal control with only loop detector data. At the same market penetration rate, signal control with CV-only data resulted in the same traffic performance, progression quality, and travel time reliability as the signal control with CV and loop detector data. Therefore, the inclusion of loop detector data did not further improve traffic operations when the CV market share reached 40%. Integrating 10% of CV data with loop detector data in the adaptive signal control improved traffic performance and travel time reliability.


2020 ◽  
Vol 47 ◽  
pp. 704-711
Author(s):  
Gorkem Akyol ◽  
Ismet Goksad Erdagi ◽  
Mehmet Ali Silgu ◽  
Hilmi Berk Celikoglu

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